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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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?

RuSkELL: Online Language Learning Tool for Russian Language

P. 292–299.
Apresyan V., Baisa V., Buivolova O., Kultepina O., Малолетняя А. П.

RuSkELL ("Russian + Sketch Engine for Language Learning") is a new online resource intended for researchers and learners of Russian. It incorporates a specially pre-processed corpus and the interface which allows users to search for phrases in sentences, extract salient collocates and show similar words. The tool builds upon its English counterpart SkELL (Baisa & Suchomel 2014). The aim of the project is to adapt the existing SkELL tool to Russian, improve its performance and make it user-friendly to Russian users. The existing problems include errors in query output and insufficiently transparent interface. The project aspires to solve them by 1) modifying Sketch grammar rules to exclude irrelevant output and to add informative collocations unaccounted for in the existing Sketch grammar; 2) providing collocation groups with easy-to-understand labels in Russian. We describe the process of building the language data and problems we need to address to accommodate the tool for the specificities of the Russian language.

Language: English
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Keywords: collocationssketchesonline language tool

In book

Proceedings of the XVII EURALEX International Congress. Lexicography and Linguistic Diversity (6 – 10 September, 2016)
Tbilisi: Ivane Javakhishvili Tbilisi State University, 2016.
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